Biology subjects

Hon, C.-C.

Publications and source records attributed to Hon, C.-C..

At least 19 recordsLinked to original sources

bioRxiv2026

Federated single-cell QTL meta-analysis reveals novel disease mechanisms

Genetic effects on gene expression are often cell type-specific and obscured in bulk analyses. To resolve this context-dependent regulation, we performed a federated cis-eQTL meta-analysis across 12 PBMC datasets (2,032 individuals, 2.5 million cells). Across six immune cell types, we identified cis-eQTLs for 6,592 genes and fine-mapped 14,985 independent loci. Notably, the 42% of eQTLs that were undetected in a bulk eQTL study on 43,301 whole blood samples also showed stronger enrichment for disease GWAS loci. We further identified three genome-wide significant and 65 suggestive loci affecting the abundance of (rare) immune cell types and validated these using previously reported hematological GWAS and bulk-derived trans-eQTLs. Integrating single-cell cis-eQTLs with bulk trans-eQTLs enabled us to anchor 6,382 trans-eGenes (37.2% novel) to upstream regulators and reconstruct directed gene regulatory relationships. For example, a hemorrhoidal disease-associated variant showed a CD4+ T cell-specific cis-eQTL on BACH1 that colocalized with 45 immune and metabolic trans-eGenes. These results demonstrate the power of single-cell QTL meta-analysis in interpreting complex trait genetics.

genetics↗

bioRxiv2025

Chromatin organizer ASCL1 governs gene programs in thymic epithelial cells, defining immunological self

Immunological self-tolerance depends on medullary thymic epithelial cells (mTECs), which express a broad repertoire of self-antigens to support negative selection of autoreactive T cells and the development of regulatory T cells. Although the autoimmune regulator AIRE is essential for this process, additional factors are required to establish the full mTEC gene expression program. Because thymoma is frequently associated with autoimmunity, implicating defective thymic tolerance, we performed single-cell RNA sequencing of TECs from thymoma patients and identified the transcription factor ASCL1 as selectively downregulated in tumor mTECs. Deletion of Ascl1 in mouse TECs resulted in spontaneous autoimmunity without inducing thymic tumorigenesis. Transcriptomic and chromatin accessibility analyses revealed that ASCL1 influences mTEC gene expression programs and is associated with corresponding changes in chromatin accessibility. Genetic interaction analyses further suggested that ASCL1 activity in immature mTECs modulates the AIRE dependency of gene expression in mature mTECs. Together, these findings identify ASCL1 as a key regulator of mTEC function and central tolerance, providing insight into mechanisms that safeguard immune homeostasis and whose disruption may contribute to autoimmune disease.

immunology↗

bioRxiv2025

A genome-wide, machine learning-guided exploration of the cis-regulatory code involved in neuronal differentiation

Gene expression is controlled by proximal and distal cis-regulatory elements (CREs), containing DNA motifs bound by various transcription factors (TFs). Other sequence features, such as specific k-mers or low complexity regions, have also been implicated [1-3]. However, in a dynamic biological process such as cell differentiation, we lack an understanding of how the transcriptional activity of CREs progressively change and what sequence features underlie these transitions, which may reflect common and/or coordinated regulatory processes. Here, we use single-cell ATAC-seq and RNA-seq to follow, at a genome scale, CREs along differentiation of induced pluripotent stem cells into cortical neurons and develop a method to automatically identify the diversity of CRE profiles and their underlying sequence features. We propose a machine-learning guided clustering algorithm, STOIC (Statistical learning TO Inform Clustering), that jointly learns an unsupervised clustering of the CREs in the space of the activity profiles and a supervised predictor associated with each cluster in the DNA-sequence space. STOIC is specifically designed to provide readily interpretable results. We show that the method identifies CRE profiles associated with highly predictive sequence features and outperforms methods solely concerned with co-activity clustering on this task. Orthogonal data collected in the same settings link the inferred CRE clusters to specific enhancer or promoter signatures. Furthermore, we show that the DNA features unveiled by STOIC reflect biologically relevant regulators and offer a valuable basis to dissect elements of the cisregulatory grammar. Finally, we demonstrate the general applicability of STOIC by analyzing five bulk CAGE datasets of human cells responding to various treatments.

bioinformatics↗

bioRxiv2025

Systematic evaluation of single-cell multimodal data integration for comprehensive human reference atlas.

The integration of multimodal single-cell data enables comprehensive organ reference atlases, yet its impact remains largely unexplored, particularly in complex tissues. We generated a benchmarking dataset for the renal cortex by integrating 3 and 5 scRNA-seq with joint snRNA-seq and snATAC-seq, profiling 119,744 high-quality nuclei/cells from 19 donors. To align cell identities and enable consistent comparisons, we developed the interpretable machine learning tool scOMM (single-cell Omics Multimodal Mapping) and systematically assessed integration strategies. "Horizontal" integration of scRNA and snRNA-seq improved cell-type identification, while "vertical" integration of snRNA-seq and snATAC-seq had an additive effect, enhancing resolution in homogeneous populations and difficult-to-identify states. Global integration was especially effective in identifying adaptive states and rare cell types, including WFDC2-expressing Thick Ascending Limb and Norn cells, previously undetected in kidney atlases. Our work establishes a robust framework for multimodal reference atlas generation, advancing single-cell analysis and extending its applicability to diverse tissues.

genomics↗

bioRxiv2024

CFC-seq: identification of full-length capped RNAs unveil enhancer-derived transcription

Long-read sequencing has transformed transcriptome profiling, yet capturing full-length, non-polyadenylated transcripts like enhancer RNAs (eRNAs) remains challenging. Here, we introduce CFC-seq, combining cap-trapping and in vitro poly(A)-tailing to sequence poly(A) and non-poly(A) RNAs with precise transcription start site. Paired with our assembler, SALA, we identified 39,425 novel transcriptional units, including [~]24,000 eRNAs. Our data reveal a distinct genomic code governing eRNA fate dictated by core promoter architecture. CpG-island enhancers show high chromatin connectivity but yield short, exosome-sensitive RNAs. Conversely, TATA-box enhancers systematically co-opt LTR retrotransposons to inherit structural motifs that produce long, stable, and spliced RNAs. Mechanistically, the pioneer factor NF-Y activates these viral elements to license transcription, balanced by TEAD4 activity across a dual-gear regulatory axis. Finally, non-poly(A) eRNAs terminate via exosome-associated processing at structural-depleted cleavage zones. This comprehensive annotation links enhancer sequence architecture to RNA fate, providing a new transformative framework for decoding the functional human genome. HighlightsO_LIExpanded genomic architecture: CFC-seq unmasks a hidden layer of human transcriptome, identifying 39,425 novel transcriptional units with high-confidence TSS support, including [~]24,000 eRNAs. C_LIO_LITSS-first assembler: We introduce SALA, a specialized long-read assembler that prioritizes authentic 5 Cap-trapped ends to accurately reconstruct the TSS-resolved transcript models. C_LIO_LIGenomic code of eRNA fate: CGI enhancers drive short and exosome-sensitive transcripts associated with repressive H3K27me3 mark and high chromatin connectivity. TATA-box enhancers produce cell-type-specific, long, stable, and frequently spliced eRNAs. C_LIO_LIEvolutionary co-option of retrotransposons: A major fraction of TATA-box eRNAs originate from LTR retrotransposons, providing a direct mechanism for integration of viral elements into the human regulatory landscape. C_LIO_LIA dual-gear pioneering axis: The pioneer factor NF-Y activates unprimed LTR-TATA enhancers to license transcription independent of histone acetylation cascades, operating in parallel with TEAD4-mediated activation. C_LIO_LIStructural determinants of eRNA termination: Non-poly(A) eRNA TES features a secondary structure depletion zone that coordinates pol II termination and calibrates exosome-mediated turnover. C_LI

genomics↗

bioRxiv2024

Integrative Transcriptomics Reveals Layer 1 Astrocytes Altered in Schizophrenia

Schizophrenia is one of the most prevalent psychiatric disorders with unclear pathophysiology despite a century-long history of intense research. Schizophrenia affects multiple networks across different brain regions. The anterior cingulate cortex (ACC) is the region that connects the limbic system to cognitive areas such as the prefrontal cortex and represents a pivotal region for the etiology of schizophrenia; however, the molecular pathology, considering its cellular and anatomical complexity, is not well understood. Here, we performed an integrative analysis of spatial and single-nucleus transcriptomics of the postmortem ACC of people with schizophrenia, together with a thorough histological analysis. The data revealed major transcriptomics signatures altered in schizophrenia, pointing at the dysregulation of glial cells, primarily in astrocytes. We further discovered a decrease in the cellular density and abundance of processes of interlaminar astrocytes, a subpopulation of astrocytes specific to primates that localize in the layer 1 and influence the superficial cortical microenvironment across layer 1 and layers 2/3 of the cortex. Our study suggests that aberrant changes in interlaminar astrocytes could explain the cell-to-cell circuit alterations found in schizophrenia and represent novel therapeutic targets to ameliorate schizophrenia-associated dysfunction.

neuroscience↗

bioRxiv2023

Quantification of the escape from X chromosome inactivation with the million cell-scale human single-cell omics datasets reveals heterogeneity of escape across cell types and tissues

One of the two X chromosomes of females is silenced through X chromosome inactivation (XCI) to compensate for the difference in the dosage between sexes. Among the X-linked genes, several genes escape from XCI, which could contribute to the differential gene expression between the sexes. However, the differences in the escape across cell types and tissues are still poorly characterized because no methods could directly evaluate the escape under a physiological condition at the cell-cluster resolution with versatile technology. Here, we developed a method, single-cell Level inactivated X chromosome mapping (scLinaX), which directly quantifies relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA-sequencing (scRNA-seq) data. The scLinaX and differentially expressed genes analyses with the scRNA-seq datasets of [~]1,000,000 blood cells consistently identified the relatively strong degree of escape in lymphocytes compared to myeloid cells. An extension of scLinaX for multi-modal datasets, scLinaX-multi, suggested a stronger degree of escape in lymphocytes than myeloid cells at the chromatin-accessibility level with a 10X multiome dataset. The scLinaX analysis with the human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes identified the larger effect sizes of the PRKX gene locus-lymphocyte counts association in females than males. This could suggest evidence of the underlying impact of escape on the genotype-phenotype association in humans. Overall, scLinaX and the quantified catalog of escape identified the heterogeneity of escape across cell types and tissues and would contribute to expanding the current understanding of the XCI, escape, and sex differences in gene regulation.

genomics↗

bioRxiv2023

CamoTSS: analysis of alternative transcription start sites for cellular phenotypes and regulatory patterns from 5' scRNA-seq data

Five-prime single-cell RNA-seq (scRNA-seq) has been widely employed to profile cellular transcriptomes, however, its power of analysing transcription start sites (TSS) has not been fully utilised. Here, we present a computational method suite, CamoTSS, to precisely identify TSS and quantify its expression by leveraging the cDNA on read 1, which enables effective detection of alternative TSS usage. With various experimental data sets, we have demonstrated that CamoTSS can accurately identify TSS and the detected alternative TSS usages showed strong specificity in different biological processes, including cell types across human organs, the development of human thymus, and cancer conditions. As evidenced in nasopharyngeal cancer, alternative TSS usage can also reveal regulatory patterns including systematic TSS dysregulations.

bioinformatics↗

bioRxiv2022

Monopogen: single nucleotide variant calling from single cell sequencing

Distinguishing how genetics impact cellular processes can improve our understanding of variable risk for diseases. Although single-cell omics have provided molecular characterization of cell types and states on diverse tissue samples, their genetic ancestry and effects on cellular molecular traits are largely understudied. Here, we developed Monopogen, a computational tool enabling researchers to detect single nucleotide variants (SNVs) from a variety of single cell transcriptomic and epigenomic sequencing data. It leverages linkage disequilibrium from external reference panels to identify germline SNVs from sparse sequencing data and uses Monovar to identify novel SNVs at cluster (or cell type) levels. Monopogen can identify 100K~3M germline SNVs from various single cell sequencing platforms (scRNA-seq, snRNA-seq, snATAC-seq etc), with genotyping accuracy higher than 95%, when compared against matched whole genome sequencing data. We applied Monopogen on human retina, normal breast and Asian immune diversity atlases, showing that that derived genotypes enable accurate global and local ancestry inference and identification of admixed samples from ancestrally diverse donors. In addition, we applied Monopogen on ~4M cells from 65 human heart left ventricle single cell samples and identified novel variants associated with cardiomyocyte metabolic levels and epigenomic programs. In summary, Monopogen provides a novel computational framework that brings together population genetics and single cell omics to uncover genetic determinants of cellular quantitative traits.

bioinformatics↗

bioRxiv2022

The high-throughput perturbation of long non-coding RNA reveals functional features in stem cells and across cell-types

Within the scope of FANTOM6 consortium, we perform a large-scale knockdown of 200 long non-coding RNAs (lncRNAs) in human induced pluripotent stem (iPS) cells, and systematically characterize their roles in self-renewal and pluripotency. We find 36 lncRNAs (18%) exhibiting cell growth inhibition From the knockdown of 123 lncRNAs with transcriptome profiling, 36 lncRNAs (29.3%) show molecular phenotypes. Integrating the molecular phenotypes with chromatin-interaction assays further reveals cis- and trans-interacting partners as potential primary targets. Additionally, cell type enrichment analysis identifies lncRNAs associated with pluripotency while the knockdown of LINC02595, CATG00000090305.1 and RP11-148B6.2 modulates colony formation of iPS cells. We compare our results with previously published fibroblasts phenotyping data and find that 2.9% of the lncRNAs exhibit consistent cell growth phenotype, whereas we observe 58.3% agreement in molecular phenotypes. This highlights molecular phenotyping is more comprehensive in revealing affected pathways.

genomics↗

bioRxiv2021

Profiling of transcribed cis-regulatory elements in single cells

Profiling of cis-regulatory elements (CREs, mostly promoters and enhancers) in single cells allows the interrogation of the cell-type and cell-state-specific contexts of gene regulation and genetic predisposition to diseases. Here we demonstrate single-cell RNA-5'end-sequencing (sc-end5-seq) methods can detect transcribed CREs (tCREs), enabling simultaneous quantification of gene expression and enhancer activities in a single assay at no extra cost. We showed enhancer RNAs can be detected using sc-end5-seq methods with either random or oligo(dT) priming. To analyze tCREs in single cells, we developed SCAFE (Single Cell Analysis of Five-prime Ends) to identify genuine tCREs and analyze their activities (https://github.com/chung-lab/scafe). As compared to accessible CRE (aCRE, based on chromatin accessibility), tCREs are more accurate in predicting CRE interactions by co-activity, more sensitive in detecting shifts in alternative promoter usage and more enriched in diseases heritability. Our results highlight additional dimensions within sc-end5-seq data which can be used for interrogating gene regulation and disease heritability.

genomics↗

bioRxiv2021

Functional annotation of human long noncoding RNAs using chromatin conformation data

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Studying lncRNAs is challenging due to their low expression level, cell type-specific occurrence, poor sequence conservation between orthologs, and lack of information about RNA domains. LncRNAs direct the regulatory factors in the locations that are in cis to their transcription sites. We designed a model to predict if an lncRNA acts in cis based on its features and trained it using RNA-chromatin interaction data. The trained model is cell type-independent and does not require RNA-chromatin data. Combining RNA-chromatin and Hi-C data, we showed that lncRNA-chromatin binding sites are determined by chromosome conformation. For each lncRNA, the spatially proximal genes were identified as their potential targets by combining Hi-C and Cap Analysis Gene Expression (CAGE) data in 18 human cell types. RNA-protein and RNA-chromatin interaction data suggested that lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. We provide the data through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

genomics↗

bioRxiv2020

Single-cell transcriptomics, scRNA-Seq and C1 CAGE discovered distinct phases of pluripotency during naïve-to-primed conversion in mice

BackgroundTwo types of mammalian pluripotent stem cells (PSC), i.e. naive and primed possess distinct cellular characteristics. It is largely unknown how these differences are generated during naive-to-primed transition process. We have established a robust in vitro transition system using a Wnt inhibitor for the first time and analyzed dynamic changes in cellular status via single-cell RNA-sequencing and C1 CAGE analyses. ResultsAnalysis of known marker genes suggested that the cell transition process progresses as expected. However, cluster analyses revealed a sudden increase in expression profile diversities three and four days after induction of the transition. These expression diversities can be reconciled by the presence of two subpopulations with distinct transcription profiles emerging at these time points. One of the subpopulations appears transiently, and surprisingly these cells showed a global downregulation of gene expression. Moreover, initiation of random X chromosome inactivation (XCI) coincides with the appearance of these transient cells. The other subpopulation can be maintained as a stem cell line and possesses expression profiles more similar to those of primed epiblast stem cells (EpiSC) than embryonic stem cells (ESC). However, there are important differences in gene expression related to epithelial-mesenchymal transition (EMT), suggesting that this subpopulation may represent a novel pluripotent state that has an intermediate cellular phenotype between ESC and EpiSC. ConclusionsThese findings should contribute to our understanding of the establishment and maintenance of distinct differentiation statuses of mammalian PSCs and provide new insights into the pluripotency spectrum in general.

genomics↗

bioRxiv2020

Inducing Human Retinal Pigment Epithelium-like Cells from Somatic Tissue

Regenerative medicine relies on basic research to find safe and useful outcomes that are only practical when cost-effective. The human eyeball requires the retinal pigment epithelium (RPE) for support and maintenance that interfaces the neural retina and the choroid at large. Nearly 200 million people suffer from age-related macular degeneration (AMD), a blinding multifactor genetic disease among other retinal pathologies related to RPE degradation. Recently, autologous pluripotent stem cell-derived RPE cells were prohibitively expensive due to time, therefore we developed a new simplified cell reprogramming system. We stably induced RPE-like cells (iRPE) from human fibroblasts by conditional overexpression of broad plasticity and lineage-specific pioneering transcription factors. iRPE cells showed features of modern RPE benchmarks and significant in-vivo integration in transplanted chimeric hosts. Herein, we detail the iRPE system with comprehensive modern single-cell RNA (scRNA) sequencing profiling to interpret and characterize its best cells. We anticipate that our system may enable robust retinal cell induction for regenerative medicine research and affordable autologous human RPE tissue for cell therapy.

bioengineering↗

bioRxiv2020

Non-allelic homologous recombination of Alu and LINE-1 elements generates somatic complexity in human genomes.

Millions of Alu and L1 copies in our genomes contribute to evolution and genetic disorders via non-allelic homologous recombination, but the somatic extent of these rearrangements has not been systematically investigated. Here we combine short and long DNA reads sequencing of repeat elements with a new bioinformatic pipeline to show that somatic recombination of Alu and L1 elements is common in human genomes. We report new tissue-specific recombination hallmarks, and show that retroelements acting as recombination hotspots are enriched in centromeres and cancer genes. We compare recombination profiles in human induced pluripotent stem cells and differentiated neurons and show that neuron-specific recombination of repeat elements accompanies chromatin changes during cell-fate determination. Finally, we find that somatic recombination profiles are altered in Parkinsons and Alzheimers disease, indicating a link between retroelements recombination and genomic instability in neurodegeneration. This work shows that somatic recombination of repeat elements contributes massively to genomic diversity in health and disease.

genomics↗

bioRxiv2020

LESR2 is a lymphatic endothelial-specific lncRNA that governs cell proliferation and migration through KLF4 and SEMA3C

Recent studies have revealed the importance of long noncoding RNAs (lncRNAs) as tissue-specific regulators of gene expression. There is ample evidence that distinct types of vasculature undergo tight transcriptional control to preserve their structure, identity, and functions. We determined, for the first time, the global lineage-specific lncRNAome of human dermal blood and lymphatic endothelial cells (BECs and LECs), combining RNA-Seq and CAGE-Seq. A subsequent genome-wide antisense oligonucleotide-knockdown screen of a robust set of BEC- and LEC-specific lncRNAs identified LETR1 as a critical gatekeeper of the global LEC transcriptome. Deep RNA-DNA, RNA-protein, and phenotype rescue analyses revealed that LETR1 acts as a nuclear trans-acting lncRNA modulating, via key epigenetic factors, the expression of essential target genes, including KLF4 and SEMA3C, governing the growth and migratory ability of LECs. Together, our study provides new evidence supporting the intriguing concept that every cell type expresses precise lncRNA signatures to control lineage-specific regulatory programs.

genomics↗

bioRxiv2018

C1 CAGE detects transcription start sites and enhancer activity at single-cell resolution

Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, most of these methods focus on the 3-end of polyadenylated transcripts and provide only a partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of transcript 5-ends with an original sample multiplexing strategy in the C1 microfluidic system. We first quantified the performance of C1 CAGE and found it as accurate and sensitive as other methods in C1 system. We then used it to profile promoter and enhancer activities in the cellular response to TGF-{beta} of lung cancer cells and discovered subpopulations of cells differing in their response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets of cells with transcripts arising from either strand within a single-cell in a mutually exclusive manner, which was validated using single molecule fluorescence in-situ hybridization.

genomics↗

bioRxiv2018

Chromatin accessibility landscape of articular knee cartilage reveals aberrant enhancer regulation in osteoarthritis

BackgroundOsteoarthritis (OA) is a common joint disorder with increasing impact in an aging society; however, there is no cure or effective treatments so far due to lack of sufficient understanding of its pathogenesis. While genome-wide association studies (GWAS) and DNA methylation profiling identified many non-coding loci associated to OA, the interpretation of them remains challenging.\n\nMethodsHere, we employed Assay for Transposase-Accessible Chromatin with high throughput sequencing (ATAC-seq) to map the accessible chromatin landscape in articular knee cartilage of OA patients and to identify the chromatin signatures relevant to OA.\n\nResultsWe identified 109,215 accessible chromatin regions in cartilage and 71% of these regions were annotated as enhancers. We found these accessible chromatin regions are enriched for OA GWAS single nucleotide polymorphisms (SNPs) and OA differentially methylated loci, implying their relevance to OA. By linking these enhancers to their potential target genes, we have identified a list of candidate enhancers that may be relevant to OA. Through integration of ATAC-seq data with RNA-seq data, we identified genes that are altered both at epigenomic and transcriptomic levels. These genes are enriched in pathways regulating ossification and mesenchymal stem cell (MSC) differentiation. Consistently, the differentially accessible regions in OA are enriched for mesenchymal stem cell-specific enhancers and motifs of transcription factor families involved in osteoblast differentiation (e.g. bZIP and ETS).\n\nConclusionsThis study marks the first investigation of accessible chromatin landscape on clinically relevant hard tissues and demonstrates how accessible chromatin profiling can provide comprehensive epigenetic information of a disease. Our analyses provide supportive evidence towards the model of endochondral ossification-like cartilage-to-bone conversion in OA knee cartilage, which is consistent with the OA characteristic of thicker subchondral bone. The identified OA-relevant genes and their enhancers may have a translational potential for diagnosis or drug targets.

genomics↗